WmXML: A System for Watermarking XML Data

As increasing amount of data is published in the form of XML, copyright protection of XML data is becoming an important requirement for many applications. While digital watermarking is a widely used measure to protect digital data from copyright offences, the complex and flexible construction of XML data poses a number of challenges to digital watermarking, such as re-organization and alteration attacks. To overcome these challenges, the watermarking scheme has to be based on the usability of data and the underlying semantics like key attributes and functional dependencies. In this paper, we describe WmXML, a system for watermarking XML documents. It generates queries from essential semantics to identify the available watermarking bandwidth in XML documents, and integrates query rewriting technique to overcome the threats from data re-organization and alteration. In the demonstration, we will showcase the use of WmXML and its effectiveness in countering various attacks.

Verifying Completeness of Relational Query Answers from Online Servers

10.1145/1330332.1330337ACM Transactions on Information and System Security11

Direct Neighbor Search

In this paper we study a novel query type, called direct neighbor query. Two objects in a dataset are direct neighbors (DNs) if a window selection may exclusively retrieve these two objects. Given a source object, a DN search computes all of its direct neighbors in the dataset. The DNs define a new type of affinity that differs from existing formulations (e.g., nearest neighbors, nearest surrounders, reverse nearest neighbors, etc) and finds application in domains where user interests are expressed in the form of windows, i.e., multi-attribute range selections. Drawing on key properties of the DN relationship, we develop an I/O optimal processing algorithm for data indexed with a spatial access method. In addition to plain DN search, we also study its K-DN and all-DN variants. The former relaxes the DN condition – two objects are K-DNs if a window query may retrieve them and only up to K − 1 other objects – whereas the all-DN variant computes the DNs of every object in the dataset. Using real, large-scale data

Privacy-Preserving Similarity-Based Text Retrieval

Article No.: 4</p